Bayesian inference
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Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available.
It is named after Thomas Bayes.
Description
Bayesian inference is an important technique in statistics, and especially in mathematical statistics.
Bayesian updating is particularly important in the dynamic analysis of a sequence of data.
Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, and law.
In the philosophy of decision theory, Bayesian inference is closely related to subjective probability, often called "Bayesian probability".
See also
- Bayes' theorem
- Bayesian Analysis, the journal of the ISBA
- Bayesian hierarchical modeling
- Bayesian probability
- Inductive probability
- Bayesian Structural Time Series (BSTS)
- International Society for Bayesian Analysis (ISBA)
- Jeffreys prior
- Monty Hall problem
- Thomas Bayes
External links
- Bayesian inference @ Wikipedia
